An observational, prospective study exploring the use of heart rate variability as a predictor of clinical outcomes in pre-hospital ambulance patients.

Objective: To explore the use of pre-hospital heart rate variability (HRV) as a predictor of clinical outcomes such as hospital admission, intensive care unit (ICU) admission and mortality. We also implemented an automated pre-analysis signal processing algorithm and multiple principal component analysis (PCA) for outcomes.

Materials And Methods: We conducted a prospective observational clinical study at an emergency medical services (EMS) system in a medium sized urban setting in the United States.

Nonlinear analysis of EMG signals - a chaotic approach.

This paper aims to present a systematic characterisation of the electromyogram (EMG) signal using a nonlinear chaotic approach. EMG signals from 10 muscles in the leg during walking and maximum voluntary contraction (MVC) were obtained and pre-processed using wavelet based denoising techniques. All signals were tested for non-linearity, stationarity and determinism.